Kitset.io allows anyone to build cross platform apps without the need to code. They use some pretty cool AI techniques to fill in the gaps between people and machines.

Graduates of the recent Lightning Lab Auckland programme, they’ve built kitsets for the hospitality vertical (restaurants and cafes) as well as Fast Moving Consumer Goods (FMCG – retail consumer products like groceries), and are in the process of expanding out into a wide variety of classes of apps.

Building your app is super easy, and if you get stuck, there’s always an AI chatbot to help you out. Deploying the app is even easier – one click, and you get an Android app, an iOS app, a mobile web site, a landing page, and a dashboard. If you’ve ever commissioned mobile app development, you’ll know that it usually takes months to complete if you can find a dev that’s willing to take you on, and it’s rare to walk away with change from $10K. Kitset lets you design your own app and deploy it in hours, and it costs only $69/month – that’s disruptive.

NIck Mitchell

The idea for Kitset was born when CEO and founder Nick Mitchell was working at Accenture in London as a senior IT architect in the telecommunications industry. He would regularly tell his customers about the power of analytics, the future of social, and how machine learning and AI would change the way people do business – AI would be as revolutionary as the Internet itself.

At the same time, Nick was irritated by how long it took and how expensive it was to build apps – he felt that a lot of innovation was being curbed by unnecessary complexity and skills requirements. So he left Accenture and started creating a platform that would let anyone build an app. He spent the next 18 months proving out the technology he wanted to unleash on this task.

Nick’s general concept for bootstrapping this idea involved three steps:

Build a tool to build apps that’s so easy to use that anyone could do it.

Teach a machine to use the tool.

Teach the machine to understand natural language (English) instructions from a human, so that the machine acts like a software developer.

The system can now do simple tasks like “please change that to a blue background” or “send a txt message when this button is pressed”. The next phase of AI implementation will be to ask questions like “are there any apps or sites that you like the look of”, and then provide a template that draws from the design of the specified apps or sites.

Dominic Trang

Lead Developer Dominic Trang has a background in Android game development. His previous gig was with pharma company Sagitto where he worked on image processing software to detect counterfeit pills. They’ve spent two years together now building the tool, which is learning from the real world 24 hours a day.

Kitset’s market entry plan has four pillars. The most important one which they’re working on right now is strategic partnerships. They’ve recently closed a deal with ASB Bank focusing on restaurants and cafes as a beta test. Why? ASB knows that apps are a big pain point for their customers, and see Kitset as a massive value add at a low cost.

The second pillar of market entry is channel partnerships. They’re working with well known and some not so well known digital agencies to reduce their cost of providing great apps and web sites to their customers. Using Kitset, agencies can do a lot of heavy lifting quickly. There are a huge number of APIs you can clip together in an app, but it’s a right pain in the proverbial to wrap a sexy UI around them. Kitset makes this easy.

The third pillar is direct sales. These are high touch at the moment, but the platform is nearly ready for use by the general business public.

And the fourth pillar is bigger ecosystem players, especially large hosting and service providers, like Microsoft Azure, AWS, or Digital Ocean. One could imagine the likes of Dropbox, 99 Designs, or Basecamp being interested in a product like this as well. Kitset drives traffic, usage, and brand leverage through these partners, who could also become potential acquirers.

In the short term however, they’re looking for additional strategic partnerships with banks and telcos, especially outside of New Zealand. All the while, they’re building up their secret-sauce protectable IP, their AI stack.

Post Lightning Lab, Kitset are putting together a small bridging round with people close to the company to last them through the rest of 2016. Early next year, once they’ve proven their technology and start getting some real traction, they’ll be doing a seed round with typical NZ seed round parameters to start scaling overseas. Keep an eye out at your local angel network for these guys.

Meantime, they’re looking for another developer who wants to get in on the ground floor building up this really interesting technology. If Javascript is your thing and you’re a MEAN (Mongo, Express, Angular, Node) developer, do get in touch with them.

How’s this for a business model: attract the top talent in a tough industry, and solve their most pressing problem. That’s exactly what Parrot Analytics is doing, and although it’s early days, so far they’re onto a winner.

The problem they’re solving is measuring the demand for TV content across the current highly fragmented landscape. Their solution enables producers and distributors to measure the performance of their content across geographical markets, and also to compare specific programmes against their competitors within a market – across all channels, traditional, streaming, even offline. Content buyers can use this information to ensure that they’re getting the best bang for the buck. Their mission is to help TV executives make better content decisions, and to better connect content creatives to consumers.

This problem is a hard one. In the olden days before the Internet, Nielsen had set-top boxes which recorded all of a viewer’s activity, but it isn’t so simple any more. You might watch a programme on live TV, then switch over to Netflix or Lightbox, Google Play, Amazon Video, Hulu, and even God forbid torrent an episode that you’re geoblocked out of. Parrot’s solution very cleverly doesn’t care how you’re consuming the content – it’s more concerned with how much buzz it’s generating in various online platforms, which turns out to be a much better and accurate measure of the demand for content.

Their system uses artificial intelligence, natural language processing, and machine learning techniques to evaluate public reaction to each piece of content, and all of this complexity is reduced to a single number to rate the value of the content: the Demand Rating™ – one metric to rule them all.

Wared Seger

Chris Riddell

Co-founded by Wared Seger and Chris Riddell, the Parrot Analytics team is a mashup of the creme-de-la-creme of NZ’s top business, data, and science people, and funded by investors across New Zealand, Australia, and the US.
The Exec Team also includes CTO Jason Hunter, VP Product Arturas Vedrickas, and Ops Manager Dil Khosa.

One of their big customers is the BBC, for whom they were able to help uncover untapped opportunities for Dr Who in South Korea [see The Economist’s case study]. Nobody had predicted that, and the good doctor has turned out to be a big hit south of the DMZ.

Parrot Analytics has plans to apply the same technology across the entertainment vertical, as it works equally well for movies, music, ebooks, and games – but the biggest pain market pain and opportunity right now is in TV.

They’ve grown from six to 15 FTE over the last year, and raised both a seed round and a “pre-series-A” round, both among the largest that have ever been raised in NZ. They’re likely to raise another larger round in 2016.